Data Clustering Algorithms and Applications

In this book, top researchers from around the world cover the entire area of clustering, from basic methods to more refined and complex data clustering approaches. They pay special attention to recent issues in graphs, social networks, and other domains. The book explores the characteristics of clus...

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Hlavní autori: Aggarwal, Charu C., Reddy, Chandan K.
Médium: E-kniha Kniha
Jazyk:English
Vydavateľské údaje: Boca Raton CRC Press 2014
CRC Press LLC
Chapman & Hall
Vydanie:1
Edícia:Chapman & Hall/CRC data mining and knowledge discovery series
Predmet:
Cluster analysis
Data mining
Document clustering
File organization (Computer science)
Machine theory
Gene Expression Time Series Data
Data Set
Latent Dirichlet Allocation
High Dimensional Scenario
LDA Model
Internal Validation Measures
Spectral Clustering
Suffix Tree
Subspace Clustering Algorithm
Semisupervised Clustering
NMF Algorithm
Frequent Item Set
NMF
Consensus Clustering
Agglomerative Hierarchical Clustering
Matrix Factorization Methods
High Dimensional Data
Cluster Ensembles
Graph Partitioning
DBSCAN Algorithm
MCL
Clustering Algorithm
UCI Dataset
Subspace Clustering
Agglomerative Hierarchical Clustering Algorithm
ISBN:9781466558212, 1466558210
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Popis
Shrnutí:In this book, top researchers from around the world cover the entire area of clustering, from basic methods to more refined and complex data clustering approaches. They pay special attention to recent issues in graphs, social networks, and other domains. The book explores the characteristics of clustering problems in a variety of application areas. It also explains how to glean detailed insight from the clustering process--including how to verify the quality of the underlying clusters--through supervision, human intervention, or the automated generation of alternative clusters.
Bibliografia:Includes bibliographical references and index
ISBN:9781466558212
1466558210
DOI:10.1201/9781315373515